BibSonomy publications for /author/O'LearyFri Feb 10 00:00:00 CET 2012IJOM125-37Investigating the Impact of Entrepreneurship Online Teaching on Science and Technology Degrees on Students Attitudes in Developing Economies: The Case of Egypt.22012dblp Wed Feb 08 00:00:00 CET 2012SIAM J. Scientific Computing63175-3200Windowed Spectral Regularization of Inverse Problems.332011dblp Wed Feb 08 00:00:00 CET 2012SIAM J. Scientific Computing63132-3152Designing Optimal Spectral Filters for Inverse Problems.332011dblp Thu Feb 02 00:00:00 CET 2012IJDSST41-13Social Media in DMSS System Development and Management.32011dblp Mon Jan 16 00:00:00 CET 2012ICISconf/icis/2011SYSCO's Best Business Practices (BBP).2011dblp Fri Dec 16 00:00:00 CET 2011UAIconf/uai/1994447-453Models of Consensus for Multiple Agent Systems.1994dblp Wed Nov 30 00:00:00 CET 2011IEEE Visualizationconf/visualization/200418Interactive Poster: Grid-Enabled Collaborative Scientific Visualization Environment.2004dblp Tue Nov 29 11:36:06 CET 2011Computers in Biology and Medicine5583 - 600Statistical correlations and risk analyses techniques for a diving dual phase bubble model and data bank using massively parallel supercomputers382008decompression diving statistical Linking model and data, we detail the LANL diving reduced gradient bubble model (RGBM), dynamical principles, and correlation with data in the LANL Data Bank. Table, profile, and meter risks are obtained from likelihood analysis and quoted for air, nitrox, helitrox no-decompression time limits, repetitive dive tables, and selected mixed gas and repetitive profiles. Application analyses include the EXPLORER decompression meter algorithm, NAUI tables, University of Wisconsin Seafood Diver tables, comparative NAUI, PADI, Oceanic NDLs and repetitive dives, comparative nitrogen and helium mixed gas risks, USS Perry deep rebreather (RB) exploration dive,world record open circuit (OC) dive, and Woodville Karst Plain Project (WKPP) extreme cave exploration profiles. The algorithm has seen extensive and utilitarian application in mixed gas diving, both in recreational and technical sectors, and forms the bases forreleased tables and decompression meters used by scientific, commercial, and research divers. The LANL Data Bank is described, and the methods used to deduce risk are detailed. Risk functions for dissolved gas and bubbles are summarized. Parameters that can be used to estimate profile risk are tallied. To fit data, a modified Levenberg–Marquardt routine is employed with L 2 error norm. Appendices sketch the numerical methods, and list reports from field testing for (real) mixed gas diving. A Monte Carlo-like sampling scheme for fast numerical analysis of the data is also detailed, as a coupled variance reduction technique and additional check on the canonical approach to estimating diving risk. The method suggests alternatives to the canonical approach. This work represents a first time correlation effort linking a dynamical bubble model with deep stop data. Supercomputing resources are requisite to connect model and data in application.Thu Nov 24 00:00:00 CET 2011ECISconf/ecis/1997618-632Business Process Re-engineering/organisational Transformation: Some Empirical Evidence From UK and Irish Organisations.1997dblp Wed Nov 23 00:00:00 CET 2011ECISconf/ecis/20021097-1100Panel: The impact of IT on accounting and auditing.2002dblp Mon Nov 21 00:00:00 CET 2011EMNLPconf/emnlp/2011467-473Ranking Human and Machine Summarization Systems.2011dblp Thu Nov 17 18:04:06 CET 2011Journal of Computational and Graphical Statistics1pp. 67-96Confidence Intervals for Discrete Approximations to Ill-Posed Problems31994Laplace_inversion ill-posed_problems inverse_problems statistics We consider the linear model Y = Xβ + ε that is obtained by discretizing a system of first-kind integral equations describing a set of physical measurements. The n vector β represents the desired quantities, the m × n matrix X represents the instrument response functions, and the m vector Y contains the measurements actually obtained. These measurements are corrupted by random measuring errors ε drawn from a distribution with zero mean vector and known variance matrix. Solution of first-kind integral equations is an ill-posed problem, so the least squares solution for the above model is a highly unstable function of the measurements, and the classical confidence intervals for the solution are too wide to be useful. The solution can often be stabilized by imposing physically motivated nonnegativity constraints. In a previous article (O'Leary and Rust 1986) we developed a method for computing sets of nonnegatively constrained simultaneous confidence intervals. In this article we briefly review the simultaneous intervals and then show how to compute nonnegativity constrained one-at-a-time confidence intervals. The technique gives valid confidence intervals even for problems with m < n. We demonstrate the methods using both an overdetermined and an underdetermined problem obtained by discretizing an equation of Phillips (Phillips 1962).Mon Nov 07 00:00:00 CET 2011IEEE Software112-14The Most Cited IEEE Software Articles.262009dblp Mon Oct 31 00:00:00 CET 2011IEEE Intelligent Systems124-25Guest Editors' Introduction: Knowledge Management - An Interdisciplinary Approach.162001dblp Mon Oct 31 00:00:00 CET 2011IEEE Intelligent Systems144-49How Knowledge Reuse Informs Effective System Design and Implementation.162001dblp Thu Oct 27 00:00:00 CEST 2011IEEE Trans. Computers1117-122Systolic Arrays for Matrix Transpose and Other Reorderings.361987dblp Thu Oct 27 00:00:00 CEST 2011IEEE Trans. Computers111355-1359From Determinacy to Systaltic Arrays.361987dblp Tue Oct 25 00:00:00 CEST 2011Int. Syst. in Accounting, Finance and Management2-3121-144The Use of Social Media in the Supply Chain: Survey and Extensions.182011dblp Fri Oct 21 00:00:00 CEST 2011Decision Support Systems4821-830Blog mining-review and extensions: "From each according to his opinion".512011dblp Mon Sep 26 00:00:00 CEST 2011EuroSPIconf/eurospi/2011191-202Communications in Computer and Information ScienceProcess Support for Product Line Application Engineering.1722011dblp